Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)

<Previous Article In Volume
Next Article In Volume>

Enhancing Physical Wellness Through Real-Time Fitness Training Solutions

Authors
M. Gurupriya1, *, Sai Kumar1, V. Tarun1, K. Rishi Sai Reddy1, K. C. Rohit2
1Department of Computer Science and Engineering, Amrita School of Computing, Amrita Vishwa Vidyapeetham, Bengaluru, Karnataka, India
2Standard Chartered Global Business Services, Bengaluru, Karnataka, India
*Corresponding author. Email: m_gurupriya@blr.amrita.edu
Corresponding Author
M. Gurupriya
Available Online 23 May 2025.
DOI
10.2991/978-94-6463-718-2_51How to use a DOI?
Keywords
Artificial intelligence; computer vision; fitness monitoring; OpenCV; pose estimation; Python; real-time systems
Abstract

We have developed a state-of-the-art fitness training system based on OpenCV and Python technologies. a novel approach motivating users to exercise by optimizing their routines with real-time pose estimation The CPU-based algorithms used efficiently detects and follow a minimum number of important body landmarks during physical activities predicting the angle of joints thereby enabling real-time feedback on posture and precision of movement. This allows users to correct their form on the fly and possibly prevent injuries. Standard webcams are compatible with the system, allowing it to be put to use for many different types of fitness platforms. This study addresses key layers for implementing a neural accelerator using an IoT device, benchmarking their performance while demonstrating the potential in practical application scenarios, making them an inexpensive and flexible substitute to traditional personal fitness coaching.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)
Series
Advances in Computer Science Research
Publication Date
23 May 2025
ISBN
978-94-6463-718-2
ISSN
2352-538X
DOI
10.2991/978-94-6463-718-2_51How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - M. Gurupriya
AU  - Sai Kumar
AU  - V. Tarun
AU  - K. Rishi Sai Reddy
AU  - K. C. Rohit
PY  - 2025
DA  - 2025/05/23
TI  - Enhancing Physical Wellness Through Real-Time Fitness Training Solutions
BT  - Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)
PB  - Atlantis Press
SP  - 587
EP  - 595
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-718-2_51
DO  - 10.2991/978-94-6463-718-2_51
ID  - Gurupriya2025
ER  -